The central theme of this dissertation is the analysis of risky choice. The first two chapters analyze the choice behavior of contestants in a TV game show named “Deal or No Deal” (DOND). DOND provides a unique opportunity to study risk behavior, because it is characterized by very large and wide-ranging stakes, by a simple probability distribution, and by stop-go decisions that require minimal skill or strategy. The first chapter analyzes individual editions from different countries. The results are hard to reconcile with expected utility theory and point to reference-dependent alternatives such as prospect theory. The choices of contestants can be explained in large part by previous outcomes experienced during the game. Risk aversion decreases after earlier expectations have been shattered by unfavorable outcomes or surpassed by favorable outcomes. The second chapter compares across editions. Risky choice turns out to be highly sensitive to the context, as defined by the initial prizes in the game. Even though the initial stakes of the various editions are widely different, contestants respond in a similar way to the stakes relative to their initial level. The third chapter of this thesis analyzes random task incentive systems (RTISs), using experiments that mimic DOND. RTISs are commonly applied in risky choice experiments to implement real incentives, especially when research budgets are limited and to avoid income effects. We find that caution is warranted when applying RTISs.

, , , , , , , , , , ,
, ,
Erasmus University Rotterdam (EUR) Erasmus School of Economics (ESE) Prof.dr. D.J.C. van Dijk Dr. N.L. van der Sar Prof.dr. P.P. Wakker
J. Spronk (Jaap)
Erasmus University Rotterdam , Erasmus Research Institute of Management
ERIM Ph.D. Series Research in Management
Erasmus Research Institute of Management

van den Assem, M. (2008, October 16). Deal or No Deal? Decision Making under Risk in a Large-Stake TV Game Show and Related Experiments (No. EPS-2008-138-F&A). ERIM Ph.D. Series Research in Management. Retrieved from